In this page, we showed:
The relationship between the Marijuana use and marijuana lyric trends
Mean prevalence rates (%) of Marijuana/other than Marijuana/binge drinking use by age group
Risk perception on smoking marijuana once a month
Annual incidence of first use of marijuana
---
title: "drug dashboard"
output:
flexdashboard::flex_dashboard:
orientation: columns
vertical_layout: scroll
source_code: embed
---
In this page, we showed:
- The relationship between the Marijuana use and marijuana lyric trends
- Mean prevalence rates (%) of Marijuana/other than Marijuana/binge drinking use by age group
- Risk perception on smoking marijuana once a month
- Annual incidence of first use of marijuana
```{r setup, include=FALSE}
library(flexdashboard)
library(plotly)
library(tidyverse)
```
```{r}
songs_abuse=read_csv("./data/songs_abuse.csv")
```
Column {.tabset data-width=600}
-----------------------------------------------------------------------
### Marijuana use Vs % of marijuana lyric national level
```{r}
songs_abuse_plot=
songs_abuse%>%
filter(stname=="National", outcome=="Marijuana use in the past month")%>%
group_by(year)%>%
ggplot(aes(x = p_lyrics, y = bsae, color = agegrp)) +
geom_point() +
geom_smooth(aes(group = agegrp), se = F) +
labs(title = "Marijuana use Vs % of marijuana lyric national level",
y = "Marijuana use in the past(%)",
color = "agegroup")
ggplotly(songs_abuse_plot)
```
Column {.tabset data-width=400}
-----------------------------------------------------------------------
### Mean prevalence rates (%) of Marijuana use by age group
```{r}
marijuana_plot=
songs_abuse%>%
filter(outcome=="Marijuana use in the past month",area==0)%>%
group_by(year,agegrp)%>%
summarize(
mean_bsae = mean(bsae)
)%>%
ggplot(aes(x = year, y = mean_bsae)) +
geom_smooth(aes(color = agegrp), alpha = .5)+
labs(title = "Mean prevalence rates (%) of Marijuana use by age group",
y = "Mean prevalence rates of Marijuana use (%) ",
color = "agegroup")
ggplotly(marijuana_plot)
```
### Mean prevalence rates (%) of illicit drug other than marijuana by age group
```{r}
otherthan_marijuana_plot=
songs_abuse%>%
filter(outcome=="Illicit drugs other than marijuana use in the last month",area==0)%>%
group_by(year,agegrp)%>%
summarize(
mean_bsae = mean(bsae)
)%>%
ggplot(aes(x = year, y = mean_bsae)) +
geom_smooth(aes(color = agegrp), alpha = .5)+
labs(title = "Mean prevalence rates (%) of illicit durg other than marijuana by age group",
y = "Mean prevalence rates (%) of illicit durg other than marijuana",
color = "agegroup")
ggplotly(otherthan_marijuana_plot)
```
### Mean prevalence rates (%) of binge drinking by age group
```{r}
bingedrink_plot=
songs_abuse%>%
filter(outcome=="Binge drinking in the last month",area==0)%>%
group_by(year,agegrp)%>%
summarize(
mean_bsae = mean(bsae)
)%>%
ggplot(aes(x = year, y = mean_bsae)) +
geom_smooth(aes(color = agegrp), alpha = .5)+
labs(title = "Mean prevalence rates (%) of binge drinking in the past by age group",
y = "Mean binge drinking (%) in the past",
color = "agegroup")
ggplotly(bingedrink_plot)
```
### Risk perception on smoking marijuana once a month
```{r}
risk_plot=
songs_abuse%>%
filter(outcome=="Risk perception on smoking marijuana once a month",area==0)%>%
group_by(year,agegrp)%>%
summarize(
mean_bsae = mean(bsae)
)%>%
ggplot(aes(x = year, y = mean_bsae)) +
geom_smooth(aes(color = agegrp), alpha = .5)+
labs(title = "Risk perception on smoking marijuana by age group",
y = "Risk perception on smoking marijuana(%) ",
color = "agegroup")
ggplotly(risk_plot)
```
### Annual incidence of first use of marijuana
```{r}
incidence_plot=
songs_abuse%>%
filter(outcome=="Annual incidence of first use of marijuana",area==0)%>%
group_by(year,agegrp)%>%
summarize(
mean_bsae = mean(bsae)
)%>%
ggplot(aes(x = year, y = mean_bsae)) +
geom_smooth(aes(color = agegrp), alpha = .5)+
labs(title = "Annual incidence of first use of marijuana by age group",
y = "Annual incidence of first use of marijuana (%) ",
color = "agegroup")
ggplotly(incidence_plot)
```